"Classic Grounded Theory to Analyse Secondary Data: Reality and Reflections"
On this opportunity i would like to make a review of a journal
about “Classic Grounded Theory to Analyse Secondary Data: Reality and
Reflections”. The article of this journal has many advantages,
namely the sentence clearly and use words that are commonly used. So the
readers can more easily understand the content of the journal. But sometimes
the election of the words still created a confusion for the readers, so it’s
make the differences of opinion between the readers.
This journal draws on
the experiences of two researchers and discusses how they conducted a secondary
data analysis using classic grounded theory. The aim of the primary study was
to explore first-time parents’ postnatal educational needs. A subset of the
data from the primary study (eight transcripts from interviews with fathers)
was used for the secondary data analysis. The objectives of the secondary data
analysis were to identify the challenges of using classic grounded theory with
secondary data and to explore whether the re-analysis of primary data using a
different methodology would yield a different outcome. Through the process of
re-analysis a tentative theory emerged on ‘developing competency as a father’.
Challenges encountered during this re-analysis included the small dataset, the
pre-framed data, and limited ability for theoretical sampling. This re-analysis
proved to be a very useful learning tool for author 1(LA), who was a novice
with classic grounded theory.
Grounded
theory (GT) is a systematic methodology in the social sciences involving
the construction of theory through the analysis of data. Grounded
theory is a research methodology which operates almost in a reverse
fashion from social science research in the positivist tradition. Primary
data originates from a study in which a researcher collects information
him/herself to answer a particular research question. Secondary data, on the
other hand, is data that already exists (Glaser, 1963). Consequently, the
secondary data analyst is not involved in the recruitment of participants or in
the collection of the data. Secondary data analysis is the use of previously
collected data, for some other purpose. It is not a method of data analysis,
therefore methods such as grounded theory or statistical analysis, for example,
can be applied to the process of secondary data analysis. The focus of classic
grounded theory is on identifying the participants’ main concern and how they
resolve that concern.
We can
make a conclusion from the journal that the comparison between primary and
secondary data analysis outcomes are when the primary and secondary data
analysis findings are compared, there are some similarities and also some
notable differences. The similarities include the fathers’ sense of not being
involved by midwives, their lack of access to knowledge and skills and their
adaptation to fatherhood although a change, it was a gradual one. Some of the
notable differences in the classical grounded theory approach include: the move
away from mere description of the data, the clear identification of a main
concern and the conceptualisation of five processes used by fathers to resolve
their concern. One explanation for the differences in the findings is the two
different ways in which this data was examined. In the primary study, a
specific pre-framed research question was applied whereas, in the secondary
data analysis, a more open analytical approach was used allowing ideas to
emerge from the data. In addition, the focus of the primary study was on
postnatal educational needs, whereas the secondary data analysis had no
preconceived framework. In the classical approach there was also a greater
emphasis, during data analysis, on transcending and conceptualising as opposed
to describing. There are two reasons for these differences, firstly, the
application of the classic grounded theory approach which utilises a more open
perspective and secondly, the passage of time facilitated a more objective
approach to analysing the data.
Strauss
(1987) recommends the use of integrative diagrams, as a way of integrating
threads of the emergent theory and as a means of explaining ideas to others.
However Glaser (1998) is of the view that diagrams oversimplify the theory, and
may result in people not reading the intricacies of the theory developed. As a
diagram had proved, in the first set of analysis, to be a useful tool in
helping to visualise relationships between categories (see figure 1), it was
decided to produce a diagram for the secondary analysis (figure 2). What is
clear from both diagrams is that neither is sufficient to explain the outcome;
however, interestingly the diagram produced from the secondary data analysis
does give a greater feel for a core concern and how the various categories
identified connected with that core concern.
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